Universität zu Köln

Kruse, Johannes ORCID: 0000-0002-3478-3379, Schaefer, Benjamin and Witthaut, Dirk ORCID: 0000-0002-3623-5341 (2021). Revealing drivers and risks for power grid frequency stability with explainable AI. Patterns, 2 (11). AMSTERDAM: ELSEVIER. ISSN 2666-3899

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Abstract

Stable operation of an electric power system requires strict operational limits for the grid frequency. Fluctuations and external impacts can cause large frequency deviations and increased control efforts. Although these complex interdependencies can be modeled using machine learning algorithms, the black box character of many models limits insights and applicability. In this article, we introduce an explainable machine learning model that accurately predicts frequency stability indicators for three European synchronous areas. Using Shapley additive explanations, we identify key features and risk factors for frequency stability. We show how load and generation ramps determine frequency gradients, and we identify three classes of generation technologies with converse impacts. Control efforts vary strongly depending on the grid and time of day and are driven by ramps as well as electricity prices. Notably, renewable power generation is central only in the British grid, while forecasting errors play a major role in the Nordic grid.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Kruse, Johannes UNSPECIFIED orcid.org/0000-0002-3478-3379 UNSPECIFIED Schaefer, Benjamin UNSPECIFIED UNSPECIFIED UNSPECIFIED Witthaut, Dirk UNSPECIFIED orcid.org/0000-0002-3623-5341 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-591152
DOI:	10.1016/j.patter.2021.100365
Journal or Publication Title:	Patterns
Volume:	2
Number:	11
Date:	2021
Publisher:	ELSEVIER
Place of Publication:	AMSTERDAM
ISSN:	2666-3899
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language WIND POWER; SYSTEM; TRANSPARENCY; GENERATION; INERTIA; PLANTS; IMPACT Multiple languages Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Interdisciplinary Applications Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/59115